当前位置:首页 >英文主页 >中英对照 > 报告详情

Talkwalker:2023年Blue Silk™GPT消费智能白皮书(英文版)(17页).pdf

上传人: 白**** 编号:119240 2023-03-21 17页 9.80MB

下载:

报告标签

GPT消费智能白皮书

1、Talkwalkers Blue Silk GPT for consumer intelligence:New way of generating insightsBlue Silk AI white paperThe first breakthrough in AI was in the computer vision field thanks to the appearance of CNN models 2(Convolutional Neural Network),the use of backward propagation techniques3 and most importan

2、tly,larger datasets,and training those models on GPU(Graphical Processing Units)cards.In 2012,during the ImageNet Large Scale Visual Recognition Challenge,the AlexNet 4 model,combining all the above methods,drastically reduced the top-5 error rate to 15.3%,more than 10 percent lower than the other m

3、odels in the competition.In the following years,with each improvement in the architecture such as new activation functions 5 or batch normalization 6 layers,the modern state-of-the-art CNN models exceeded human performance and recently surpassed the top-5 error rate with an astonishing 99%accuracy l

4、evel 7.This staggering quantitative improvement put the field on the map and launched the artificial intelligence boom.However,even though AI was booming,its Natural Language Processing(NLP)subfield was still waiting for its revolution,namely pre-trained language models.A language model is a probabi

5、lity distribution over a sequence of words.More specifically,it outputs a probability that represents the validity of the input sentence.Those models can be used for a large number of problems.However,so far,they performed relatively poorly and each model was trained for a specific task and could no

6、t be used for other purposes.In 2017,the Transformer architecture 8 composed of self-attention layers was introduced,and it changed radically the possibilities in the field.Introduction The history of AI often dates back to the early days of computing when machines were first used to perform simple

word格式文档无特别注明外均可编辑修改,预览文件经过压缩,下载原文更清晰!
三个皮匠报告文库所有资源均是客户上传分享,仅供网友学习交流,未经上传用户书面授权,请勿作商用。
本文主要介绍了大型语言模型(LLM)的发展历程、能力以及应用。 1. 大型语言模型(LLM)的发展历程:从最早的CNN模型到Transformer架构,再到BERT模型,LLM在自然语言处理(NLP)领域取得了重大突破。随着模型参数和训练数据的增加,LLM在理解自然语言和生成高质量文本方面取得了显著进步。 2. LLM的能力:LLM具有强大的理解和生成能力,能够处理各种NLP任务,如文本摘要、机器翻译、文本分类等。此外,LLM还具有零样本学习和少样本学习的能力,能够通过简单的提示快速适应新的任务。 3. LLM的应用:LLM在消费者情报和社会监听领域具有广泛的应用。例如,Talkwalker的Blue Silk™ Insight技术利用LLM从大量评论和评论中提取关键见解,而Blue Silk™ AI Classifiers则利用LLM的零样本分类能力对数据进行分类。 4. LLM的挑战:虽然LLM具有巨大的潜力,但在实际应用中仍面临一些挑战,如模型的训练、访问和正确请求的制定。
大型语言模型如何改变消费者情报? 大型语言模型在实际应用中面临哪些挑战? 大型语言模型如何助力企业探索新市场?
客服
商务合作
小程序
服务号
折叠